access icon free Congestion management of power system with uncertain renewable resources and plug-in electrical vehicle

© The Institution of Engineering and Technology
Received 30/10/2018, Accepted 18/12/2018, Revised 07/12/2018, Published 07/01/2019

The study describes the quantifying impact of plug-in electrical vehicles (PEVs) and renewable energy sources (RES) for congestion management of power system. The proposed congestion management problem is formulated considering uncertainties of wind, solar, number of PEVs and load condition over a day. The uncertainty modelling of solar, wind and PEVs is presented using beta, Rayleigh and normal distribution functions, respectively. The PEVs uncertainty is dependent on its number and increases with escalation in number. The degree of uncertainties of RES is dependent on corresponding variable (wind and solar). These uncertainties result in large number of scenarios which increases the computational burden. The k-means clustering algorithm is applied to reduce the number of scenarios. The objective function is formulated to minimise generation cost, rescheduling cost and PEV cost for congestion management. This system is analysed by using Monte Carlo simulation. The proposed methodology relieves the congestion and reduces the generation cost, total power generation, total loss with increasing number of PEVs. The test result indicates that PEVs not only act as small storage unit but it also provides power during peak hours. The proposed approach is modelled in GAMS environment and implemented on modified IEEE 39-bus system.

Inspec keywords: Monte Carlo methods; normal distribution; power generation economics; power markets; wind power plants; power generation scheduling; renewable energy sources; electric vehicles; power system management; solar power stations

Other keywords: plug-in electrical vehicle; congestion management problem; modified IEEE 39-bus system; beta function; Rayleigh distribution functions; rescheduling cost minimization; k-means clustering algorithm; uncertainty modelling; total power generation; generation cost minimization; PEV uncertainty; renewable energy sources; Monte Carlo simulation; uncertain renewable resources; power system; PEV cost minimization; GAMS environment; RES; normal distribution functions

Subjects: Solar power stations and photovoltaic power systems; Wind power plants; Power system planning and layout; a.c. transmission; Transportation; Monte Carlo methods; Power system management, operation and economics

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